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Developing Additive Spectral Approach to Fuzzy Clustering
2011
MiNa11a
An additive spectral method for fuzzy clustering is presented. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which allows us to draw several stopping rules to the procedure. We experimentally test the performance of our method and show its competitiveness.
In proceedings
Boris Mirkin, Susana Nascimento
S.O. Kuznetsov, D. Ślęzak, D. Hepting, B. Mirkin
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
LNCS
Springer-Verlag
-
6743
273-277
978-3-642-21880-4
-
-
http://www.springerlink.com/content/w7164453r6914069/
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Boris Mirkin and Susana Nascimento, Developing Additive Spectral Approach to Fuzzy Clustering, in: S.O. Kuznetsov and D. Ślęzak and D. Hepting and B. Mirkin (eds), Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, LNCS, Springer-Verlag, Vol. 6743, ISBN 978-3-642-21880-4, Pag. 273-277, (http://www.springerlink.com/content/w7164453r6914069/), 2011.
Boris Mirkin and <a href="/people/members/view.php?code=4d69262d034cb8174d039bea8d970836" class="author">Susana Nascimento</a>, <b>Developing Additive Spectral Approach to Fuzzy Clustering</b>, in: S.O. Kuznetsov, D. Ślęzak, D. Hepting and B. Mirkin (eds), <u>Rough Sets, Fuzzy Sets, Data Mining and Granular Computing</u>, LNCS, Springer-Verlag, Vol. 6743, ISBN 978-3-642-21880-4, Pag. 273-277, (<a href="http://www.springerlink.com/content/w7164453r6914069/" target="_blank">url</a>), 2011.
@inproceedings {MiNa11a, author = {Boris Mirkin and Susana Nascimento}, editor = {S.O. Kuznetsov and D. Ślęzak and D. Hepting and B. Mirkin}, title = {Developing Additive Spectral Approach to Fuzzy Clustering}, booktitle = {Rough Sets, Fuzzy Sets, Data Mining and Granular Computing}, series = {LNCS}, publisher = {Springer-Verlag}, volume = {6743}, pages = {273-277}, isbn = {978-3-642-21880-4}, url = {http://www.springerlink.com/content/w7164453r6914069/}, abstract = {An additive spectral method for fuzzy clustering is presented. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which allows us to draw several stopping rules to the procedure. We experimentally test the performance of our method and show its competitiveness.}, year = {2011}, }
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